In STAT 201 - Statistical Inference for Data Science, we conducted a group project to study:
Is there a significant difference in the weather record of the 1950s and the 2000s in terms of temperature and precipitation?
We sampled from a weather station in BC, and examined two variables: daily temperature and yearly maximum rainfall over two category: historical and contemporary. Hypothesis testing and confidence interval are applied. Method of computer simulation by bootstrap and asymptotic are used to compare the test results.
Summary of one test results:
Null Hypothesis:
The difference between the population mean of the contemporary daily temperature and the historical daily temperature is zero.
Alternative Hypothesis:
The difference between the population mean of the contemporary daily temperature and the historical daily temperature is not zero.
| Test Statistic | Observed Test Statistic | Method | p-value | Lower CI | Upper CI |
|---|---|---|---|---|---|
| 1.258 | Simulation | <0.001 | 1.048 | 1.465 | |
| 1.258 | Asymptotic | <0.001 | 1.055 | 1.461 |
The p-value is < 0.001, we reject the null hypothesis
in favor of
at the 5% significant level.
There is a significant difference betweenand
.
Please feel free to explore our final report for detailed analysis and result discussion. Available in file format of ipynb and html.